POLLY — PERFORMING POLYHEDRAL OPTIMIZATIONS ON A LOW-LEVEL INTERMEDIATE REPRESENTATION 论文

2012Parallel Processing Letters引用 341
Parallel Computing and Optimization TechniquesEmbedded Systems Design TechniquesDistributed and Parallel Computing Systems

详细信息

发表期刊/会议
Parallel Processing Letters
发表日期
2012-12-01
发表年份
2012

关键词

Parallel Computing and Optimization TechniquesEmbedded Systems Design TechniquesDistributed and Parallel Computing Systems

摘要

The polyhedral model for loop parallelization has proved to be an effective tool for advanced optimization and automatic parallelization of programs in higher-level languages. Yet, to integrate such optimizations seamlessly into production compilers, they must be performed on the compiler's internal, low-level, intermediate representation (IR). With Polly, we present an infrastructure for polyhedral optimizations on such an IR. We describe the detection of program parts amenable to a polyhedral optimization (so-called static control parts), their translation to a Z-polyhedral representation, optimizations on this representation and the generation of optimized IR code. Furthermore, we define an interface for connecting external optimizers and present a novel way of using the parallelism they introduce to generate SIMD and OpenMP code. To evaluate Polly, we compile the PolyBench 2.0 benchmarks fully automatically with PLuTo as external optimizer and parallelizer. We can report on significant speedups.